Data quality aspects of administrative data

This course will provide an introduction to data quality, and how it can affect all aspects of working with administrative data. The course will cover data quality dimensions which include technical and social aspects.

As researchers and practitioners working with administrative data, we are often given datasets where we do not know the full provenance about how this dataset was captured, what kind of processing has been applied to it, and if it has been linked or merged with data from other sources. Complete and up-to-date metadata are not always available. Not fully understanding the provenance of a dataset can lead to assumptions and misconceptions being made about the content and quality of the dataset. This can result in incorrect processing and/or analysis of a dataset which potentially can lead to bad outcomes and decision making.

This course will provide an introduction to data quality and its impact on all aspects of working with administrative data, and will cover data quality dimensions including technical considerations, social factors, frameworks used to assess or quantify data quality, real-world examples and case studies showing how poor data quality can harm data science projects, practical recommendations for improving data quality awareness, and interactive sessions where participants can share experiences of how data quality challenges have affected their own projects.

This one-day course is aimed both at researchers and practitioners who are working with administrative data, as well as those who are involved in the management of data centric systems in organisations that act as data custodians, or who are involved in the capture, processing, and linkage of data that potentially will be used for administrative data research. 

The course requires little technical knowledge, and all technical background will be introduced during the course. The course will be a mixture of four hours of interactive presentations (containing small practical exercises) plus two one-hour sessions with group discussions.